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United States Patent |
5,325,026
|
Lyons
,   et al.
|
June 28, 1994
|
Microprocessor-based commutator for electronically commutated motors
Abstract
A commutator for an electronically commutated machine provides a
microprocessor-based mechanism for translating discrete samples of machine
angular rotor position information, either measured or determined
indirectly, into commutation signals. Commutation control is achieved with
shaft position information available only at discrete time instants, which
are not, in general, the required commutation times. A filter and state
observer provide estimates of the mechanical states of the rotating
machine, i.e., angular position, velocity and acceleration. In one
embodiment, a Kalman filter of variable gain is used for estimating the
mechanical states. In another embodiment, a sliding mode observer is used
for estimating the mechanical states. In the preferred embodiment, a
combination of a sliding mode observer and a steady state Kalman filter is
used to obtain the mechanical state estimates; the Kalman filter with
small constant gains provides smooth tracking of a steadily rotating
machine, while the sliding mode observer provides fast acquisition during
transient conditions.
Inventors:
|
Lyons; James P. (Niskayuna, NY);
MacMinn; Stephen R. (Schenectady, NY);
Pradeep; Anantha K. (Clifton Park, NY)
|
Assignee:
|
General Electric Company (Schenectady, NY)
|
Appl. No.:
|
906173 |
Filed:
|
June 29, 1992 |
Current U.S. Class: |
318/254; 318/439; 318/561 |
Intern'l Class: |
G11B 021/08 |
Field of Search: |
318/701,802,803,805,807,809,561,254,432,632,439,138,798
|
References Cited
U.S. Patent Documents
3883785 | May., 1975 | Fulcher et al. | 318/254.
|
4366422 | Dec., 1982 | Rhodes | 318/632.
|
4442393 | Apr., 1984 | Abbondanti | 318/805.
|
4458321 | Jul., 1984 | Whitney et al. | 318/561.
|
4499413 | Feb., 1985 | Izosima et al. | 318/802.
|
4639651 | Jan., 1987 | Shimizu | 318/432.
|
4713745 | Dec., 1987 | Schauder | 318/809.
|
4739240 | Apr., 1988 | MacMinn et al. | 318/696.
|
4772839 | Sep., 1988 | MacMinn et al. | 318/696.
|
4792870 | Dec., 1988 | Pinson | 318/561.
|
5097190 | Mar., 1992 | Lyons et al. | 318/701.
|
5107195 | Apr., 1992 | Lyons et al. | 318/701.
|
5128813 | Jul., 1992 | Lee | 318/561.
|
Other References
"A State Observer for the Permanent-Magnet Synchronous Motor", Jones et
al., Proceedings of IECON '87, Nov. 2-6, Cambridge, Mass.
"Variable Reluctance Machine Control", M. Chow, PhD Thesis, Cornell
University, Department of Electrical Engineering, Aug. 1987.
"A State Observer for Variable Reluctance Motors: Analysis and
Experiments", Lumsdaine et al. Proceedings of the 19th Asilomar Conference
on Circuits, Systems & Computers, Pacific Grove, Calif., Nov. 6-8, 1985.
"State Observers for Variable Reluctance Motors", A. Lumsdaine et al., IEEE
Transactions on Industrial Electronics, vol. 37, No. 2, Apr. 1990, pp.
133-142.
"A Simple Motion Estimator for Variable-Reluctance Motors", Harris et al.,
IEEE Transactions on Industry Applications, vol. 26, No. 2, Mar./Apr.
1990, pp. 237-243.
|
Primary Examiner: Shoop, Jr.; William M.
Assistant Examiner: Cabeca; John W.
Attorney, Agent or Firm: Breedlove; Jill M., Snyder; Marvin
Claims
What is claimed is:
1. A commutator for an electronically commutated machine, comprising:
input means for sampling noisy angular position measurements;
state observer means for processing each respective noisy angular position
measurement and generating therefrom discrete estimates of mechanical
states of the machine, said mechanical states including at least shaft
position and velocity, said state observer means comprising a Kalman
filter of variable gain; and
signal processing means for generating phase commutation signals from said
discrete estimates for commutating each respective phase of said
electronically commutated machine, said signal processing means comprising
commutation predictor means for determining a next commutation instant for
each respective phase based on said discrete estimates and generating
timing signals corresponding thereto, said signal processing means further
comprising timer means for receiving said timing signals and generating
commutation signals to each respective phase for commutation at the
commutation instants determined by said commutation predictor means.
2. The commutator of claim 1 wherein said state observer means further
generates a discrete estimate of acceleration from said noisy position
estimates.
3. A commutator for an electronically commutated machine, comprising:
input means for sampling noisy angular position measurements;
state observer means for processing each respective noisy angular position
measurement and generating therefrom discrete estimates of mechanical
states of the machine, said mechanical states including at least shaft
position and velocity, said state observer means comprising a Kalman
filter of variable gain; and
signal processing means for generating phase commutation signals from said
discrete estimates for commutating each respective phase of said
electronically commutated machine, said signal processing means comprising
a phase-locked loop, including interpolated-counter means, for generating
an interpolated position estimate between discrete state estimates for
each respective phase, said signal processing means further comprising
commutation signal generating means for receiving said interpolated
position estimates and generating commutation signals to each respective
phase for commutation at the interpolated position determined by said
interpolator-counter means.
4. A commutator for an electronically commutated machine, comprising:
input means for sampling noisy angular position measurements;
state observer means for processing each respective noisy position
measurement and generating therefrom discrete estimates of mechanical
states of the machine, said mechanical states including at least shaft
position and velocity, said state observer means comprising a sliding mode
observer; and
signal processing means for generating phase commutation signals from said
discrete estimates for commutating each respective phase of said
electronically commutated machine, said signal processing means comprising
commutation predictor means for determining the next commutation instant
for each respective phase based on said discrete estimates and generating
timing signals corresponding thereto, said signal processing means further
comprising timer means for receiving said timing signals and generating
commutation signals to each respective phase for commutation at the
commutation instants determined by said commutation predictor means.
5. A commutator for an electronically commutated machine, comprising:
input means for sampling noisy angular position measurements;
state observer means for processing each respective noisy position
measurement and generating therefrom discrete estimates of mechanical
states of the machine, said mechanical states including at least shaft
position and velocity, said state observer means comprising a sliding mode
observer; and
signal processing means for generating phase commutation signals from said
discrete estimates for commutating each respective phase of said
electronically commutated machine, said signal processing means comprising
a phase-locked loop, including interpolator-counter means, for generating
an interpolated position estimate between discrete state estimates for
each respective phase, said signal processing means further comprising
commutation signal generating means for receiving said interpolated
position estimates and generating commutation signals to each respective
phase for commutation at the interpolated position determined by said
interpolator-counter means.
6. A commutator for an electronically commutated machine, comprising:
input means for sampling noisy angular position measurements;
state observer means for processing each respective noisy position
measurement and generating therefrom discrete estimates of mechanical
states of the machine, said mechanical states including at least shaft
position and velocity, said state observer means comprising a combination
of a Kalman filter and a sliding mode observer; and
signal processing means for generating phase commutation signals from said
discrete estimates for commutating each respective phase of said
electronically commutated machine, said signal processing means comprising
commutation predictor means for determining the next commutation instant
for each respective phase based on said discrete estimates and generating
timing signals corresponding thereto, said signal processing means further
comprising timer means for receiving said timing signals and generating
commutation signals to each respective phase for commutation at the
commutation instants determined by said commutation predictor means.
7. A commutator for an electronically commutated machine, comprising:
input means for sampling noisy angular position measurements;
state observer means for processing each respective noisy position
measurement and generating therefrom discrete estimates of mechanical
states of the machine, said mechanical states including at least shaft
position and velocity, said state observer means comprising a combination
of a Kalman filter and a sliding mode observer; and
signal processing means for generating phase commutation signals from said
discrete estimates for commutating each respective phase of said
electronically commutated machine, said signal processing means comprising
a phase-locked loop, including interpolator-counter means, for generating
an interpolated position estimate between discrete state estimates for
each respective phase, said signal processing means further comprising
commutation signal generating means for receiving said interpolated
position estimates and generating commutation signals to each respective
phase for commutation at the interpolated position determined by said
interpolator-counter means.
8. The commutator of claim 3 wherein said state observer means further
generates a discrete estimate of acceleration from said noisy position
estimates.
9. The commutator of claim 4 wherein said state observer means further
generates a discrete estimate of acceleration from said noisy position
estimates.
10. The commutator of claim 5 wherein said state observer means further
generates a discrete estimate of acceleration from said noisy position
estimates.
11. The commutator of claim 6 wherein said state observer means further
generates a discrete estimate of acceleration from said noisy position
estimates.
12. The commutator of claim 7 wherein said state observer means further
generates a discrete estimate of acceleration from said noisy position
estimates.
Description
FIELD OF THE INVENTION
The present invention relates generally to state estimators for estimating
position, velocity and acceleration of a rotating machine and, more
particularly, to microprocessor-based commutation of an electronically
commutated machine which may be useful, for example, in a phase
commutation scheme without a shaft position sensor.
BACKGROUND OF THE INVENTION
Phase current commutation in electric motors is typically accomplished by
feeding back a rotor position signal to a controller from a shaft angle
transducer, e.g. an encoder or a resolver. To improve reliability and to
reduce size, weight, inertia and cost in electric motor drives, however,
it is desirable to eliminate the shaft angle transducer. In a switched
reluctance motor drive, for example, methods for indirectly determining
rotor position without using a shaft angle transducer have been described
in U.S. Pat. No. 5,097,190 of J. P. Lyons and S. R. MacMinn, and U.S. Pat.
No. 5,107,195 of J. P. Lyons, M. A. Preston and S. R. MacMinn, both
assigned to the instant assignee. Measurements from indirect rotor
position sensors may be noisy and, in general, are not continuously
available. In particular, measurements are available only at discrete
instants in time as dictated by microprocessor sampling and calculation
requirements which will not, in general, coincide with the desired
commutation times for the electric machine. Therefore, it is necessary to
process and translate such noisy position measurements into reliable phase
current commutation times occurring at the appropriate instants.
SUMMARY OF THE INVENTION
A commutator according to the present invention provides a
microprocessor-based mechanism for translating discrete samples of machine
angular rotor position information, either measured or determined
indirectly, into commutation signals for an electronically commutated
machine (ECM). Commutation control is achieved with shaft position
information available only at discrete time instants, which are not, in
general, the required commutation times.
According to the present invention, a filter and state observer provide
estimates of the mechanical states of the rotating machine, i.e., angular
position, velocity and acceleration. In one embodiment, a Kalman filter of
variable gain is used for estimating the mechanical states. In another
embodiment, a sliding mode observer is used for estimating the mechanical
states. In the preferred embodiment, a combination of a sliding mode
observer and a steady-state Kalman filter is used to obtain the mechanical
state estimates; the Kalman filter with small constant gains provides
smooth tracking of a steadily rotating machine, while the sliding mode
observer provides fast acquisition during transient conditions.
The commutator according to the present invention further comprises a means
of processing the mechanical state estimates into machine phase
commutation signals. In one embodiment, a phase-locked-loop forces a
hardware counter to track and interpolate between the discrete time
position estimates. In particular, the hardware counter's output emulates
the output of, for example, a resolver-to-digital (R/D) converter and thus
can be directly used in a variety of hardware commutation schemes. In the
preferred embodiment, commutation control software translates desired
commutation angles and mechanical state estimates into commutation event
times which are loaded into hardware counters for triggering actual phase
commutation upon expiration thereof.
The present invention may be advantageously employed within a "sensorless"
commutation scheme for an ECM, such as, for example, a switched reluctance
motor.
BRIEF DESCRIPTION OF THE DRAWINGS
The features and advantages of the present invention will become apparent
from the following detailed description of the invention when read with
the accompanying drawings in which:
FIG. 1 is a block diagram of a commutator according to the present
invention;
FIG. 2 is a block diagram of mechanical state estimator state employing a
Kalman filter useful in the commutator of FIG. 1 according to one
embodiment of the present invention;
FIG. 3 is a block diagram of mechanical state estimator state employing a
sliding mode observer useful in the commutator of FIG. 1 according to an
alternative embodiment of the present invention;
FIG. 4 is a block diagram of mechanical state estimator state employing a
combination of a Kalman filter and sliding mode observer according to the
preferred embodiment of the present invention;
FIG. 5 is a block diagram of an alternative embodiment of a commutator
according to the present invention; and
FIG. 6 is a block diagram of a phase-locked loop useful in the commutator
of FIG. 5.
DETAILED DESCRIPTION OF THE INVENTION
FIG. 1 illustrates a commutator 10 according to the present invention.
Commutator 10 receives noisy position measurements .theta..sub.ma,
.theta..sub.mb and .theta..sub.mc from a rotor position estimator (not
shown), such as, for example, of a type described in U.S. Pat. No.
5,097,190 or U.S. Pat. No. 5,107,195, cited hereinabove. The noisy
position measurements are sampled by a sample-and-hold (S&H) circuit 12
and supplied, via a multiplexer (MUX) 14, to a state estimator 16
implemented in a microprocessor 20. By way of example, the commutator of
the present invention is described with reference to a three-phase
electronically commutated motor (ECM), although it is to be understood
that the principles of the commutation scheme of the present invention are
not limited to three phases. State estimator 16 is formulated to provide
state estimates of rotor angular position .theta., velocity .omega., and
acceleration .alpha.. According to the embodiment of FIG. 1, the state
estimates of position .theta., speed .omega. and acceleration .alpha. are
provided to a commutation predictor 22 which predicts the time interval to
the next commutation event for each of the machine phases A, B and C. In
particular, the commutator predictor calculates the time to the next
commutation event t.sub.com approximately as follows:
##EQU1##
or optionally for greater accuracy as:
##EQU2##
where .theta..sub.com represents the commutation position corresponding to
the commutation time t.sub.com. The time t.sub.com for each phase is
loaded into the respective hardware commutation timer A, B or C,
respectively corresponding to phases A, B and C of the ECM, in order to
precisely determine the commutation instants of each phase. The control
logic for controlling commutator 10 is designated generally by block 24
and is shown as having control inputs to S&H 12, MUX 14, and
microprocessor 20.
FIG. 2 illustrates one embodiment of state estimator 16 comprising a Kalman
filter of variable gain which is used for both acquiring and tracking the
noisy position measurements .theta..sub.mk. The Kalman filter processes
the noisy position measurements .theta..sub.mk and generates state
estimates of position .theta..sub.k, speed .omega..sub.k, and acceleration
.alpha..sub.k. In particular, the state equations for a machine rotating
with constant angular acceleration subject to noise perturbations can be
formulated as:
x=Ax+Bw,
where w represents plant noise and
##EQU3##
Assuming noisy measurements of angular position are available, a
measurement equation can be formulated as:
z=Hx+v, where H=[1 0 0],
where measurement noise v is assumed to be white gaussian noise with zero
mean and variance R=.sigma..sub.x.sup.2.
The plant noise is assumed to be white gaussian noise with zero mean and
variance Q=.sigma..sub.a.sup.2. The unknown but bounded input to the plant
is now treated as a plant noise. In addition, it is assumed that the noise
terms v and w are uncorrelated.
The continuous state propagation equations are discretized using a
zero-order hold (ZOH) and are represented as:
x.sub.k+1 =F(.delta.t)x.sub.k +Gw.sub.k,
where
##EQU4##
The discrete samples are not necessarily regularly spaced in time;
consequently, the transition matrices are functions of .delta.t=t.sub.k+1
-t.sub.k, where t.sub.k and t.sub.k+1 represent the sampling instants.
The measurement equation can be represented in discrete form as:
z.sub.k =Hx.sub.k +v.sub.k, where H=[1 0 0 ].
From the discrete state and measurement equations, the Kalman filter can be
formulated to estimate the rotor angular position, velocity, and
acceleration, subject to the specified plant and measurement noises. That
is, the Kalman filter can be recursively formulated as:
.delta.t.sub.k =t.sub.k -t.sub.k-1
P.sub.k =F(.delta.t.sub.k)P.sub.k-1 F(.delta.t.sub.k) .sup.T
+G(.delta.t.sub.k)QG(.delta.t.sub.k).sup.T
K.sub.k =P.sub.k H.sup.T (HP.sub.k H.sup.T +R).sup.-1
x.sub.k =F(.delta.t.sub.k)x.sub.k-1
x.sub.k =K.sub.k (z.sub.k -Hx.sub.k)
P.sub.k =(I-K.sub.k H) P.sub.k,
where P.sub.k represents the covariance matrix of the Kalman filter; and
K.sub.k represents the Kalman gains.
Since the state variable .theta. assumes values in the range from 0 to
2.pi., it is necessary to define a consistent means of determining the
innovation .delta..sub.k from values of .theta. and .theta.. To this end,
a function .theta.mod is defined to be
.theta.mod=(.theta. mod 2.pi.)-.pi.,
where the estimation error .theta.=.theta.-.theta..
From the equation for .theta.mod, it is evident that given values of
.theta. and .theta., there are two possible values for the estimation
error .theta.. However, given bounds on rotor velocity and sampling-rate,
and assuming that the velocity estimate .omega. is close to its actual
value, it is possible to choose the appropriate value of .theta.. If the
innovations .delta..sub.k are such that two consecutive innovation errors
exceed a large bound on the error, then that innovation sequence is
dismissed, and the velocity estimate is reinitialized once again.
The Kalman filter equations set forth hereinabove are implemented according
to the block diagram of FIG. 2. In particular, each noisy measurement
.theta..sub.mk is compared in a summer 30 to the a priori predicted
measurement Hx.sub.k from a block 32. The prediction error signal output
from summer 30 is provided to block 34 for performing the .theta.mod
function thereon. The innovation signal output .gamma..sub.k from block 34
is provided to a block 36 for multiplication by the Kalman gain K.sub.k.
The output signal from block 36 is a vector correction which is added to
the a priori state vector estimate x.sub.k in a summer 38, resulting in
the a posteriori estimate x.sub.k. The estimate is delayed by a unit delay
operator 40, yielding x.sub.k-1, which is multiplied by the state
transition matrix function F(.delta.t.sub.k) in a block 42, resulting in
the a priori state estimate vector x.sub.k.
In the embodiment of FIG. 2, a thresholding technique is preferably
employed to determine whether the unmodeled inputs to the system being
tracked have changed suddenly. In particular, according to the
thresholding technique, the covariance matrix P.sub.x is reset when the
innovation signal .gamma..sub.k exceeds a predetermined value of
.epsilon., as indicated by block 44 and the dashed line in FIG. 2. It is
to be understood that the initial values of the covariance matrix P.sub.k
and the Kalman gains K.sub.k are initially chosen by the designer.
In an alternative embodiment, as illustrated in FIG. 3, state estimator 16'
comprises a sliding mode observer which is used to both acquire and track
the noisy position measurements. The sliding mode observer processes the
position measurements .theta..sub.mk and generates estimates of position
.theta., speed .omega., and acceleration .alpha..
The sliding mode observer equations are as follows:
.theta.=.omega.+l.sub..theta. .theta.+g.sub..theta. sign[.theta.]
.omega.=.alpha.+l.sub..omega. .omega.+g.sub..omega. sign[.theta.]
.alpha.=l.sub..alpha. .alpha.+g.sub..alpha. sign[.alpha.]
.theta.=.theta.mod(.theta.-.theta.)
As shown in FIG. 3, the innovation .gamma..sub.k from the .theta.mod block
34 is provided to a sign function block 50. The sign function is a
set-valued function that takes values in the closed interval [-1,1]. The
output signal from the sign function block 50 is provided to a gain block
G. In particular, using sliding mode observer theory, it can be shown that
there exists a choice of gains g.sub..theta., g.sub..omega. and
g.sub..alpha. that ensure acquisition of the state estimates. The
observer gains satisfy the following criteria:
g.sub..theta. .gtoreq..omega..sub.max ;
g.sub..omega. .gtoreq..alpha..sub.max ; and
g.sub..alpha. .gtoreq.F.sub.max,
where the variables with the subscript max refer to the maximum values that
the physical variables can assume, with F.sub.max representing the maximum
change in acceleration. In vector form,
##EQU5##
As shown in FIG. 3, the innovation .gamma..sub.k is also provided to gain
block L. The gains l.sub..theta., l.sub..omega., and l.sub.60 are linear.
In vector form,
##EQU6##
The output signals from gain blocks L and G are added together and
compared in a summer 52 to x.sub.k. For the microprocessor-based
implementation of state estimator 16', the continuous sliding mode
observer equations given hereinabove are discretized with a zero-order
hold (ZOH), as indicated in blocks L and G of FIG. 3 and as will be
appreciated by those skilled in the art.
Despite the presence of linear gains, state estimator 16' functions solely
as a sliding mode observer. The linear gains are utilized to increase the
domains of acquisition of the observer. Although the construction of the
sliding mode observer of FIG. 3 does not necessitate a thresholding
technique, such as that described hereinabove with reference to FIG. 2,
chattering may result from the high gains chosen in the conjunction with
the sliding mode. Advantageously, however, state estimator 16' is robust
with respect to noise and input perturbations.
FIG. 4 illustrates a preferred implementation of a state estimator 16' for
use in the commutator of FIG. 1. The state estimator of FIG. 4 is a
discretized combination of a sliding mode observer and a steady-state
Kalman filter, with modified observer equations. The innovation
.gamma..sub.k takes three paths, each of which employs a modified sign
function In the first path, .gamma..sub.k is provided to a block 60 which
represents the following modified sign function that incorporates a dead
zone wherein the value of the function is zero:
##EQU7##
The output signal from block 60 is provided to gain block G, described
hereinabove. In the second path, .gamma..sub.k is provided to a modified
sign block 62 which provides a linear output outside a dead zone, as
illustrated. The output signal from block 62 is provided to gain block L,
described hereinabove. In the third path, .gamma..sub.k is provided to
another modified sign block 64 where, as illustrated, the value of the
modified sign function is linear for inputs within a range defined by the
closed interval [-1,1] and is zero otherwise. The output signal from block
64 is provided to a gain block K, described hereinbelow. The output
signals from gain blocks K and L are added together in a summer 66. The
sum from summer 66 is added by a summer 68 to the output signal from gain
block G, while x.sub.k is subtracted in summer 68. The output signal from
summer 68 represents the estimate x.sub.k.
For relatively small estimation errors, the state observer of FIG. 4
functions as a Kalman filter, i.e., a linear observer with steady-state
Kalman gains K. The linear and sliding gains, denoted by L and G,
respectively, in FIG. 4, are set to zero during this phase of operation.
However, for relatively large estimation errors, the state observer of
FIG. 4 functions as a nonlinear sliding mode observer utilizing both the
linear and sliding gains L and G. Thus, the observer retains the
beneficial properties of both the Kalman filter and the sliding mode
observer without a significant increase in complexity or order of
computation.
Other modifications of the sign function are possible in the embodiment of
FIG. 4 for processing noisy position measurements and generating state
estimates of position .theta..sub.k, speed .omega..sub.k, and acceleration
.alpha..sub.k of a rotating machine, as long as the functions are
set-valued and operate in the closed interval [-1,1]. Moreover, by using
the combination of a sliding mode observer and a Kalman filter, as
illustrated in the preferred embodiment of FIG. 4, the need for a
thresholding technique is avoided.
FIG. 5 illustrates an alternative implementation of a commutator according
to the present invention wherein a phase-locked loop (PLL) is employed for
processing the mechanical state estimates (i.e., bipolar phase error
signals) into machine phase commutation signals, rather than timer-based
commutation, as illustrated in FIG. 1. In the embodiment of FIG. 5, the
PLL is partially implemented in microprocessor software and partially
implemented in hardware. The PLL software includes a loop compensator 80;
and, the PLL hardware includes a digital-to-analog D/A converter 82, a
voltage-to-frequency V/F converter 84, and an interpolator-counter 86. The
microprocessor performs the phase error detection function of the PLL; the
V/F converter performs the voltage-controlled oscillator (VCO) function of
the PLL; and the interpolator-counter 86 performs the frequency
integration function of the PLL. The microprocessor determines the phase
error after each state estimator update by comparing a sampled
interpolator angle estimate .theta..sub.i from interpolator-counter 86
with the current state estimate .theta.. The update involves generating a
new frequency command via the D/A converter. For an ideal V/F converter,
the new frequency command, after phase lock, corresponds to the velocity
.omega..
The PLL is illustrated in more detail in FIG. 6. In particular, the PLL
includes a summer 90 for comparing the angle estimate .theta. from the
state estimator with the interpolated angle output .theta..sub.i via a
sample-and-hold circuit 91. The resulting error signal is provided to loop
compensator 80, which includes a zero-order hold (ZOH) 85. The output
signal form ZOH 85 is provided to D/A converter 82. The output signal from
D/A converter 82 is converted to a frequency signal in V/F converter 84;
and interpolator-counter 86 integrates the frequency signal to provide the
interpolated angle output .theta..sub.i.
The PLL interpolator-counter is capable of running freely without
microprocessor updates for a predetermined period of time, thus allowing
the microprocessor some time for soft-error recovery as required by, for
example, a watch-dog time-out reinitialization sequence.
The output count .theta..sub.i from the interpolator-counter is preferably
maintained at a greater resolution than required for commutation purposes.
That is, the most significant output bits are used for commutation, while
the lower order bits are ignored. If sufficient lower bits are thus
reserved, effects of the PLL dynamics (i.e., oscillations of
.DELTA..theta.=.theta.-.theta..sub.i) can be relegated to these lower
order bits, thereby ensuring that the upper order bits are tracked.
As shown in FIG. 5, the output count .theta..sub.i from the
interpolator-counter is provided to a hardware commutator 90, such as that
described in commonly assigned U.S. Pat. No. 4,739,240 of S. R. MacMinn
and P. M. Szczesny, issued Apr. 19, 1988 and incorporated by reference
herein.
While the preferred embodiments of the present invention have been shown
and described herein, it will be obvious that such embodiments are
provided by way of example only. Numerous variations, changes and
substitutions will occur to those of skill in the art without departing
from the invention herein. Accordingly, it is intended that the invention
be limited only by the spirit and scope of the appended claims.
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